\begin{table}[ht]
\centering
\resizebox{.9\textwidth}{!}{
\begin{tabular}{lrrrrrr}
  \hline
Comparison & Estimate & SE & t & p-value & F-statistic & F-test p-value \\ 
  \hline
A. White vs. Black &  &  &  &  &  &  \\ 
  Monitoring vs. Control & 0.073 & 0.042 & 1.729 & 0.085 & 1.481 & 0.097 \\ 
  Punitive vs. Control & 0.036 & 0.04 & 0.897 & 0.37 & 1.263 & 0.212 \\ 
  Punitive vs. Monitoring & -0.021 & 0.048 & -0.436 & 0.663 & 0.936 & 0.532 \\ 
  B. White vs. Hispanic &  &  &  &  &  &  \\ 
  Monitoring vs. Control & 0.019 & 0.044 & 0.428 & 0.669 & 1.081 & 0.369 \\ 
  Punitive vs. Control & -0.023 & 0.04 & -0.573 & 0.567 & 2.187 & 0.004 \\ 
  Punitive vs. Monitoring & -0.045 & 0.047 & -0.944 & 0.346 & 1.293 & 0.194 \\ 
  C. Black vs. Hispanic &  &  &  &  &  &  \\ 
  Monitoring vs. Control & 0.083 & 0.043 & 1.913 & 0.056 & 1.651 & 0.049 \\ 
  Punitive vs. Control & 0.038 & 0.042 & 0.903 & 0.367 & 1.247 & 0.224 \\ 
  Punitive vs. Monitoring & -0.042 & 0.05 & -0.854 & 0.394 & 1.091 & 0.36 \\ 
   \hline
\end{tabular}
}
\caption[Predicting missingness on subjective index as a function of treatment assignment]{The estimated correlation between treatment assignment and missingness on the subjective index measure of net discrimination in interactions during appointments, estimated from OLS models regressing missingness on treatment assignment and block fixed effects with inverse probability weighting. The F-statistic and F-test p-value tests the null hypothesis that all coefficients equal zero.}
\label{predmissindex}
\end{table}
